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MI and SSVEP dual paradigm-based few-channel asynchronous control brain computer interface system

A brain-computer interface and asynchronous control technology, applied in the intersection of information processing, cognitive neuroscience, and automatic control, can solve the problems of inability to achieve asynchronous control, few-channel BCI, improved classification accuracy, and poor signal quality. Improve the classification accuracy, overcome the slow selection speed, and improve the effect of feature extraction and classification capabilities

Active Publication Date: 2018-08-28
SOUTHEAST UNIV
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  • Claims
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Problems solved by technology

[0008] The purpose of the present invention is to address the shortcomings of the above-mentioned background technology, and provide a brain-computer interface system with few channels and asynchronous control based on MI and SSVEP dual paradigms, and realize the multi-selection function of the BCI system through MI paradigm BCI and SSVEP paradigm BCI connected in series. Asynchronous control, solves the technical problems that the classification options of the MI paradigm in the few-channel BCI system are few, the SSVEP paradigm cannot realize asynchronous control, the signal quality of the few-channel BCI is poor, and the classification accuracy rate needs to be improved

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  • MI and SSVEP dual paradigm-based few-channel asynchronous control brain computer interface system
  • MI and SSVEP dual paradigm-based few-channel asynchronous control brain computer interface system
  • MI and SSVEP dual paradigm-based few-channel asynchronous control brain computer interface system

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Embodiment Construction

[0041] The technical solution of the invention will be described in detail below in conjunction with the drawings.

[0042] figure 1 This is the BCI system shown in the present invention. The system includes: a spontaneous MI instruction module for the user to spontaneously generate MI signal output, and an SSVEP stimulation module for stimulating the user's SSVEP signal, which is used to collect the user’s EEG in response to the MI and SSVEP paradigms. Signal EEG acquisition module, MEMD analysis module for multivariable empirical mode decomposition analysis of EEG signals, asynchronous control module composed of switch modules composed of MI paradigm and multi-select modules composed of SSVEP paradigm, asynchronous control module The output is the output of the BCI system.

[0043] figure 2 The middle is a schematic diagram of the asynchronous control of the BCI system proposed by the present invention. The BCI system consists of a switch module composed of MI paradigm and a mu...

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Abstract

The invention discloses an MI and SSVEP dual paradigm-based few-channel asynchronous control brain computer interface system, and belongs to the technical field of cognitive neural science, information processing and automation control crossing. For a few-channel electroencephalogram signal BCI system, an MI paradigm is adopted as a switch module of the BCI system; an SSVEP paradigm is adopted asa BCI multi-choice module; the two modules are connected in series to form the asynchronous control BCI system; a few-channel EEG signal is decomposed into multiple intrinsic mode functions by utilizing a multi-variable empirical mode decomposition algorithm; based on a spectrum distribution characteristic of MI, the IMFs are preferentially selected as characteristics for realizing MI classification; an improved canonical correlation analysis method is proposed for calculating canonical correlation coefficients between the IMFs and SSVEP frequency templates; the optimal canonical correlation coefficient is preferentially selected out for realizing SSVEP classification; and therefore, the control effect and the classification accuracy of the few-channel BCI system can be improved.

Description

Technical field [0001] The invention discloses a few-channel asynchronous control brain-computer interface system based on MI and SSVEP dual paradigms, in particular to an asynchronous control brain-computer interface system composed of two paradigms of forward and backward serial motion imagination and steady-state visual evoked potential, belonging to cognitive nerves The technical field where science, information processing, and automation control intersect. Background technique [0002] Brain-Computer Interface (BCI) is an information interaction and control channel established between the brain and the external environment. People can use this channel to control external devices through brain consciousness. The key of the BCI system is to accurately classify the brain's control consciousness, so as to realize different control commands. Effective feature extraction and classification of brain signals are key technologies related to BCI system performance indicators. The c...

Claims

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Application Information

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IPC IPC(8): G06F3/01
CPCG06F3/015
Inventor 葛盛江一川刘慧
Owner SOUTHEAST UNIV
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